Surgical planning for living donor liver transplant using 4D flow MRI, computational fluid dynamics and in vitro experiments.

IF 1.3 Q4 ENGINEERING, BIOMEDICAL

Computer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualization Pub Date : 2018-01-01 Epub Date: 2017-01-18 DOI:10.1080/21681163.2017.1278619

David R Rutkowski, Scott B Reeder, Luis A Fernandez, Alejandro Roldán-Alzate

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引用次数: 26

Abstract

Abstract This study used magnetic resonance imaging (MRI), computational fluid dynamics (CFD) modelling and in vitro experiments to predict patient-specific alterations in hepatic hemodynamics in response to partial hepatectomy in living liver donors. 4D Flow MRI was performed on three donors before and after hepatectomy and models of the portal venous system were created. Virtual surgery was performed to simulate (1) surgical resection and (2) post-surgery vessel dilation. CFD simulations were conducted using in vivo flow data for boundary conditions. CFD results showed good agreement with in vivo data, and in vitro experimental values agreed well with imaging and simulation results. The post-surgery models predicted an increase in all measured hemodynamic parameters, and the dilated virtual surgery model predicted post-surgery conditions better than the model that only simulated resection. The methods used in this study have potential significant value for the surgical planning process for the liver and other vascular territories.

Abstract Image

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活体肝移植手术计划的4D血流MRI、计算流体力学和体外实验。

本研究使用磁共振成像(MRI)、计算流体动力学(CFD)建模和体外实验来预测活体肝供者部分肝切除术后肝脏血流动力学的特异性改变。对3例肝切除术前后供体行4D血流MRI检查，建立门静脉系统模型。通过虚拟手术模拟(1)手术切除和(2)术后血管扩张。采用体内流动数据作为边界条件进行CFD模拟。CFD结果与体内数据吻合较好，体外实验值与成像和模拟结果吻合较好。术后模型预测了所有测量的血流动力学参数的增加，并且扩张的虚拟手术模型比仅模拟切除的模型更好地预测了术后情况。本研究中使用的方法对肝脏和其他血管区域的手术计划过程具有潜在的重要价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualization ENGINEERING, BIOMEDICAL-

CiteScore

2.80

自引率

6.20%

发文量

102

期刊介绍： Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization is an international journal whose main goals are to promote solutions of excellence for both imaging and visualization of biomedical data, and establish links among researchers, clinicians, the medical technology sector and end-users. The journal provides a comprehensive forum for discussion of the current state-of-the-art in the scientific fields related to imaging and visualization, including, but not limited to: Applications of Imaging and Visualization Computational Bio- imaging and Visualization Computer Aided Diagnosis, Surgery, Therapy and Treatment Data Processing and Analysis Devices for Imaging and Visualization Grid and High Performance Computing for Imaging and Visualization Human Perception in Imaging and Visualization Image Processing and Analysis Image-based Geometric Modelling Imaging and Visualization in Biomechanics Imaging and Visualization in Biomedical Engineering Medical Clinics Medical Imaging and Visualization Multi-modal Imaging and Visualization Multiscale Imaging and Visualization Scientific Visualization Software Development for Imaging and Visualization Telemedicine Systems and Applications Virtual Reality Visual Data Mining and Knowledge Discovery.